The field of the invention is the detection of features in images, and particularly, the detection of features such as edges in two-dimensional images.
There are numerous applications in which images are analyzed to locate specific features. For example, an object may be scanned with a camera and the edges of the object may be detected and used to locate the object and determine its orientation. Edge detection is also used in establishing the boundaries of an object so that it may be identified using pattern recognition methods, or measured. For example, an ultrasound image of the human heart may be analyzed by first locating the edges of the various heart chambers and then calculating the sizes of those chambers and the thicknesses of the chamber walls.
There are many approaches used to detect features in images. One approach is to fit a model of the feature to the image. The model is moved around the image and where there is a good match the feature location is indicated. Other methods use probabilistic measures, and most methods use filtering techniques which attempt to remove noise without obscuring the feature being detected. Filter operators such as the Roberts operator, Haar operator, Sobel operator, Canny's detector and wavelet transform are used to enhance images as a first step in feature detection, but the effectiveness of such filtering is determined by the choice of the filter scale. The choice of the filter scale may be arbitrary, or it may be based on results from prior applications of a similar nature. If the filter scale is large, filtering is intense and noise is smoothed out at the expense of lost localization of a detected feature or even failure to detect a feature. If the scale is small, on the other hand, less filtering is used and the results may be corrupted by noise which produces false alarms.